designing ad creative

So….Is That Good? The Complete Guide to Benchmarking Ad Creative

designing ad creative

Does it follow the brand book? Does it speak to the right audience? Does it abide by general design principles? 👈 These are the questions that most designers or agencies ask themselves when they’re answering the question: “so…is that good?”

But, as a creative team nestled within a growth marketing agency, we demand much, much more out of every asset that leaves our desks. 

In addition to putting our assets through the typical creative wringer, we put each through a gauntlet stacked with data. That allows us to work in-step with growth marketers and channel experts to design creative that uplifts campaign performance and, ultimately, drives revenue. 

Primary Metrics and How We Use Them

Hop into Facebook Business Manager, TikTok Ads Manager, or any of the other back-end dashboards that power your campaigns and you’ll see a wealth of data to parse through. Here are the metrics we hone in on when it comes to benchmarking creative and what they tell us about each asset:

Click-Through Rate: When we see a high CTR on an asset, we can deduce that it was attention-grabbing and compelling enough to drive our audience to click. 

Cost Per Click: Similar to CTR, CPC is a metric that helps us understand how “grabby” our creative is. The lower the CPC, the stronger the creative. 

Conversion Rate: While we use the platforms’ owned dashboards to peek at CTR and CPC, when it comes to CVR, we’re all about Google Analytics. When we see a higher CVR on a piece of creative, we can deduce that not only was the creative compelling enough to earn us a click, but also the user was equipped with enough information (and excitement!) to complete a desired action once they hit the site. Obviously, the ad creative is only part of this equation (site experience and UX is the other big-hitter when it comes to this metric) but it’s still super helpful in understanding the performance of an asset. 

Cost Per Conversion: Similar to CVR this is a metric that helps us understand how actionable our creative is. The lower the cost per conversion, the stronger the creative. 

Secondary Metrics and How We Use Them

Just the same as how the DNA of each growth marketing strategy differs, so do the KPIs and useable metrics. So, while the above four metrics are typically the most important, sometimes we don’t have the luxury of leaning on them. Instead, we can use other helpful metrics to fill in the blanks. 

Time on Site: TOS is a great substitute for conversion rate and cost per conversion for organizations with higher customer acquisition costs. 

Leads: This one is simple – instead of peeking at conversion rates, sometimes lining up the total number of leads or conversions, take a look at the hard numbers. 

Here an example of how we’ve subbed in other metrics when CTR, CPC, CVR, and CPC can’t tell the whole story:

We work with an organization with a relatively high cost per conversion. That means, with their monthly budget, sometimes we’ll only have one or two conversions on even our best-performing assets. In this case, CVR and CPC are relatively useless metrics (because they’ll only give us information on a few of our assets). To solve for this, we’ve subbed in time on site (TOS) in place of CPC and CVR.

ad creative results

Industry Benchmarks by Platform

Okay, so you’ve compiled your data, you can see which assets are driving stronger performance. But still, is it good? Take a peek at the industry benchmarks by the the most-used platforms to see how your creative measures up. We’re only including click-through rate and cost per click in the chart below because conversion rate, cost per conversion, and time on site depend so heavily on factors outside of the ad platform (like the UX of your site, cost of your product/service, etc):

Facebook (including Instagram):

  • CTR: 0.9%
  • CPC: $0.97


  • CTR: 3% to 12% CTR
  • CPC: $1.20


  • CTR: 0.55%
  • CPC: $5.58

Note: these are averages across all industries. There can be significant discrepancy depending on industry, so make sure you dive a little deeper to get the full story!

Leveraging Data to Make Better Creative

Data for data’s sake is simply a waste. So, the most important part of the entire equation is gleaning insights that make a massive impact on what you make next. While leveraging data to untangle what’s working and what’s not is a bit of an exercise in educated interpretation, overtime, it can make a massive difference. Here’s a shortened version of our process here at Tuff:

  1. Gather the growth marketer, social ads expert, and creative lead ‘round to get a big-picture view of the best performing assets and the ones that were left behind. 
  2. Identify common threads among the top three/four at the top and bottom of the pack. Investigate things like:
    1. Which value props are featured?
    2. Are there color/type similarities?
    3. What type of creative are in these groups? Videos? GIFs?
    4. What kind of content is featured? Big, bold copy? Testimonials?
  3. Articulate your high-level insights about what worked, what didn’t work as well, and how you plan to create a fresh round of assets that honors what works and leaves behind what doesn’t.

Think you could use a hand gathering and synthesizing data to make creative that doesn’t just look nice, but drives real results? Let’s talk.

A Step-by-Step Guide for Running a Chatbot Test in 2019

It’s pretty dang hard to get around the internet these days without hearing about chatbots and ‘the future of AI’. It’s a hot topic and something we’re pretty excited about.

I’m pretty strict about what I subscribe to and here is my inbox filtering for AI (so not including emails using chatbot specifically).

We’ve been learning more about what customers need and expect from their online experience, and helping clients run a chatbot test to see how the channel converts. It can serve as a great user acquisition channel, depending on your target audience.

In this post, we’ll briefly cover what opportunities a chatbot can help you take advantage. But, the true intention is to give you a framework and template for running a chatbot test on your own to see if it works well for your customers as well as employees.

Tell me more about chatbots…

Chatbots are Artificial Intelligence (AI) programs that can process and respond to simple queries from your audience like an interactive FAQ. You’ve seen them across the internet, often in the bottom right corner of a web page. It looks similar to live chat but with programmed data on the other end.

Screenshot of's homepage with a chatbot in the bottom right corner.

When a company is utilizing a chatbot, they’ve taken the time to teach the chatbot the answers to questions they expect a customer to ask.

It works a bit like a flow chart:

Examples of companies running chatbots…

  • Duolingo uses chatbots inside their language teaching app and allows users to practice conversation by simulating text exchanges. [Learn more about the bot here]
  • Apartment Ocean is a chatbot built to help real estate agents qualify leads and learn more about potential customers. [Learn more about the bot here]
  • Pizza Hut allows people to order pizzas and reorder their favorites via a Facebook messenger chatbot. [Test out their bot here]
  • Casper, a mattress company, has a purely promotional bot that is active from 11pm to 5am to ‘keep you company when you just can’t fall asleep’. While it can chat on many topics from Stranger Things to Seinfeld, it also takes the opportunity to plug their mattresses from time to time. [Learn more about the bot here]

Why should I run a chatbot test?

Do you ask customers to fill out a form?
Chatbots have helped create a shift toward something being coined as ‘conversational marketing’. You can use chatbots to replace long forms with more intuitive and natural conversations. You can set up a bot to ask those same qualifying leads your forms are searching for. Depending on the potential customer’s answers, the chatbot will send them through the right flow.

Looking to help your sales agents save time and close more leads?
A chatbot can automatically qualify leads and get them to the right agents. As research from and the Harvard Business Review shows, even if you wait just five minutes to respond after a lead first reaches out, there’s a 10x decrease in your odds of actually getting in touch with that lead. After 10 minutes, there’s a 400% decrease in your odds of qualifying that lead. By automating this crucial step, your chatbot can quickly disqualify leads and get the most promising ones quickly to your agents.

Want to improve your customer experience?
There’s never going to be a future where Artificial Intelligence totally takes over because humans and chatbots are good at different things. Leaning on our strengths and the strengths of chatbots can make for a power team. When a chatbot pilot program was initiated in a telco company, it could handle 82% of common queries in customer service. After 5 weeks of tweaking, analyzing, and optimizing by human agents, its success increased to 88%, according to Accenture.

Let’s check out the data

In the 2018 State of Chatbots study from Drift and friends, they surveyed over 1,000 internet users in the United States and made sure to match their audience to represent the U.S. adult online population. Here’s what the group had to say about their current online experiences:

In addition to helping people get quicker answers, you can use the chatbot data to make changes to your website and try to eliminate the root cause of the most frequently asked questions.

Do you have customers spanning multiple generations?: One preconceived notion I had about chatbots is that they were better suited for companies with younger target audiences. I was excited to find data saying quite the opposite. In that same 2018 State of Chatbots Study, Drift found that Baby Boomers (age 55+) were 24% more likely than Millennials (age 18-34) to expect benefits from chatbots in five of the nine following categories:

I’m in. How do I run a chatbot test?…

We feel really great about the future of chatbots and their ability to improve customer experience and to deliver higher quality leads. That being said, before jumping in with both feet we suggest running a chatbot test to validate or invalidate whether it works well for customers and team.

We’ve organized a super simple experiment to help sales teams run a chatbot test and see if it could work for them:

  • Step 1: Develop a single hypothesis about what the chatbot will deliver
  • Step 2: Explicitly Identify the metric that will help you validate or invalidate your hypothesis
  • Step 3: Get benchmark data for that metric. You may be able to pull this from your current process or will need to build time into your experiment to capture it.
  • Step 4: Test chatbot
  • Step 5: Compare the two data sets to see if your hypothesis is valid or invalid.

Here is an example chatbot test:

  • Step 1 – Hypothesis: Implementing a chatbot will decrease the amount of time it takes to make first contact with a lead.
  • Step 2 – Metric: Hours from form filled to first contact.
  • Step 3 – Benchmark data: Depending on the size of your sales team, pull the data from at least 10% of your sales agents. If you are already measuring this metric, awesome! Just pull it and proceed to Step 4. If not, spend 10 days (without the agents’ knowledge) measuring this.
  • Step 4 – Test: There are a number of chatbot solutions out there. We recommend Intercom’s 14-day free trial because it’s a lean and easy way to get started and they have great analytics. Have the same agents you used for benchmark data spend 10 days using Intercom’s chatbot to qualify and make initial contact with leads.
  • Step 5 – Compare: In a spreadsheet, take the data from your two sets of 10 days and compare your metric, ‘hours from form filled to first contact’. Which one has a lower average? Does one have a better conversion rate?

Continued reading about Chatbots:

Ready to run a chatbot test?

If you’re interested in testing out a chatbot for your sales, customer success, or customer support team, we hope this experiment helps. We’re also always available to talk through ideas and implement an experiment tailored to your team and goals. Check out a

with Tuff.

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